CN104574420A - Nanoscale shale digital core building method - Google Patents

Abstract

A nanoscale mud shale digital core construction method, comprising the following steps: (1) using FIB-SEM to cut and scan the core; (2) FIB-SEM scanning image registration; (3) angle correction; (4) shadow Correction; (5) Establishment of nanoscale mud shale digital cores. The present invention firstly selects the appropriate sub-sample area for the plunger rock sample with a diameter of 25 mm, observes with an electron microscope, selects the area of interest, and cuts the cut end face with argon ion light using focused ion beam-scanning electron microscope (FIB-SEM) The scanning technology cuts and scans the shale core samples to obtain a series of two-dimensional images of the core, and then uses the image registration technology to align the two adjacent images of the acquired images, and uses the shear transformation to correct the angle of the images. The gray scale processing technology is used to correct the shadow of the image, and finally the digital core of mud shale with nanoscale resolution is constructed.

Description

A nanoscale shale digital core construction method

technical field

The invention relates to a method for constructing nano-scale mud shale digital cores in the field of rock physics research, in particular to a set of processing methods for constructing nano-scale mud shale cores using FIB-SEM technology.

Background technique

There are two main types of modeling methods for digital cores: one is physical methods, which use experimental instruments to directly image core samples to construct digital cores, mainly including sequential two-dimensional thin section superposition imaging methods, confocal laser scanning methods, and X-ray CT scanning methods. Imaging methods; the other is mathematical methods, which are based on high-precision two-dimensional thin-section images and reconstruct three-dimensional digital cores through stochastic simulation or geological process simulation.

The digital core constructed by the confocal laser scanning method is equivalent to a pseudo-3D digital core with the thickness of a two-dimensional thin section, so it is rarely used in the actual construction of digital cores. The physical method commonly used in practical applications to construct digital cores is X-ray CT scanning imaging Methods and sequential imaging methods.

There are currently two main types of X-ray CT scanning systems used to construct digital cores of reservoir rocks, one is a desktop micro-CT scanning system that uses an industrial X-ray generator to generate X-rays; the other uses a synchrotron as an X-ray system. The synchrotron micro-CT scanning system of the ray generator. Although the current advanced desktop micro-CT scanning system can obtain digital cores with a resolution of 5um or even higher, the high-quality digital cores in the literature are all obtained with synchrotron micro-CT scanning systems. The Australian National University established a digital core laboratory in 2004, using a self-made micro-CT scanning system to conduct extensive and in-depth research on digital core construction technology, and constructed a column with a diameter of 5cm, a maximum field of view of 55mm, and a resolution of less than 2um Digital cores for plug cores.

In addition to using physical experiment methods, mathematical reconstruction algorithms can also be used to construct digital cores. At present, there are mainly stochastic methods and process simulation methods. Stochastic methods mainly include Gaussian random field method, simulated annealing method, sequential indicator simulation method, multi-point geostatistical method and Markov chain method.

In 1974, Joshi first proposed a Gaussian random field method for reconstructing 3D digital cores. In 1997, Hazlett proposed a simulated annealing method for reconstructing three-dimensional digital cores. In 2003, Keehm reconstructed a 3D digital core using the Sequential Indicative Simulation (SISIM) algorithm. The digital cores built by these three methods have poor connectivity when the porosity is low. In 2004, Okabe developed a multi-point geostatistical method for reconstructing a 3D digital core from a 2D thin section image of the core by referring to the geostatistical method commonly used in the geological modeling process. Wu et al. reconstructed a 3D digital core based on a Markov random grid statistical model. The digital cores established by these two methods have better pore connectivity. Unlike the random method that introduces random functions to reconstruct digital cores, in 1997, and Bakke reconstructed digital cores by simulating the sedimentation process, compaction process and diagenesis process of rocks using spheres with different particle radii. The pore connectivity of the digital core established by the process simulation method is good, but it is generally only suitable for the reconstruction of digital cores of simple rocks in the diagenetic process.

Judging from the numerous digital core modeling methods at present, the physical experiment method is the most accurate method for constructing digital cores, and can best reflect the microscopic pore structure of real cores. However, the same core is scanned with different resolutions, and the scanning results show that the porosity of the digital core increases gradually with the increase of the resolution. When the resolution reaches 1 μm, the porosity of the 3D digital core is still smaller than the porosity measured in the laboratory, indicating that there are micropores in the core that are smaller than the scanning resolution. The existence of micropores makes the digital core porosity lower than the experimental porosity, and affects the pore connectivity of the digital core, which is not conducive to the subsequent numerical simulation research. At present, the resolution of commonly used CT scanning is mostly micron and submicron, and it is difficult to observe the nanoscale fracture and pore system in mud shale. Due to the limitation of CT scanning resolution, it is urgent to propose a digital core of nanoscale mud shale. The construction method provides an effective medium for the study of shale reservoir pore structure and digital petrophysical properties.

Contents of the invention

(1) Purpose of the invention

The present invention provides a method for constructing nano-scale mud shale digital cores, specifically a set of technologies for establishing nano-scale mud shale digital cores by using FIB-SEM technology to cut and scan mud shale cores and subsequent processing. High rate mud shale digital cores can clearly analyze the distribution of mud shale pore structure and divide organic pores and inorganic pores.

(2) Technical solutions

A nanoscale mud shale digital core construction method. First, the FIB-SEM cutting and scanning technology is used to cut and scan the mud shale core samples to obtain a series of two-dimensional images of the core, and then image registration technology is used to image the obtained pictures. Two adjacent images are aligned, and the shear transformation is used to correct the angle of the image, and the shadow correction is used to correct the image, and finally a nano-scale resolution mud shale digital core is constructed. The specific steps are as follows:

(1) Using FIB-SEM to cut and scan the core, the steps include:

a. For the plunger rock sample with a diameter of 25 mm, select an appropriate sub-sample area, cut a thin slice with a diameter of 25 mm and a thickness of 2-5 mm, then observe with an electron microscope, select the area of interest, and perform argon ion analysis on the cut end face. Light;

b. Carry out carbon coating on the scanning end face of the rock core after polishing;

c. Grind a groove on the surface of the sample, and then use FIB-SEM technology to cut and scan the area of 15 microns x 10 microns x 10 microns;

d. Scanning and cutting are carried out alternately, and the number of slices is not less than 1000 sliced images in TIFF format;

e. The computer stores and scans the images in TIFF format, and ends the experiment when a certain number of slices is reached;

(2) FIB-SEM scanning image registration: the two-dimensional image is represented by a two-dimensional numerical matrix, and I ₁ (x, y) and I ₂ (x, y) respectively represent the two images that need to be registered. The gray value at (x, y), where I ₁ is the reference image and I ₂ is the image to be registered, then the registration relationship of images I ₁ and I ₂ can be expressed as

I ₂ (x,y)=G(I ₁ (F(x,y)))

Among them, F represents a two-dimensional coordinate transformation function; G represents a one-dimensional grayscale transformation function; the main task of image registration is to find the best coordinate transformation function F, and the grayscale transformation function G, so that the difference between the two images To achieve optimal alignment, since the grayscale transformation function G does not need to be solved in most cases, obtaining the coordinate transformation function F becomes a key issue in image registration. The above formula can be simplified to the following form:

I ₂ (x, y) = I ₁ (F(x, y))

In the process of image registration, the commonly used image transformation methods mainly include rigid body transformation, affine transformation, projective transformation and nonlinear transformation; if the distance between any two points in the image remains unchanged before and after transformation, this transformation is called It is rigid body transformation; rigid body transformation can be decomposed into overall translation and rotation; in a two-dimensional image, the transformation formula of coordinate point (x, y) to point (x′, y′) through rigid body transformation is:

in is the rotation angle, Δx and Δy are translation distances;

(3) Angle correction: During the cutting and scanning process of FIB-SEM, when the angle between the ion beam and the electron beam is not 90°, the cutting surface scanned by the scanning electron microscope cannot reflect the real size of the sample, so an angle transformation is required Transition to the state where the electron beam is perpendicular to the scanning surface can be calculated by the following formula:

$\mathrm{<span\; class="notranslate">\; AC</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; AB</span>}}{\mathrm{<span\; class="notranslate">\; cos</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 90</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; )</span>}$

Among them, α is the angle between the ion beam and the electron beam, AB is the size obtained by scanning, and AC is the real size of the sample;

(4) Shading correction: Due to the influence of the sample groove and the stage, it will cause certain interference to the SEM electronic signal, resulting in a partial shadow area in the image, that is to say, the area representing the same material phase has different gray values, so It is necessary to perform shading correction on the scanned image to ensure the accuracy of image segmentation; the correction method uses grayscale processing technology to perform shading correction on the image;

(5) Establishment of nanoscale mud shale digital core: the processed 2D images are superimposed to form a nanoscale resolution 3D mud shale digital core.

Further, the grayscale image processing technology described in step 4 is to take out the grayscale value of each pixel in the picture, and then set the red, green, and blue components of the color of this point as grayscale values; grayscale value=red ×0.30+green×0.59+blue×0.11; obtaining the color of a certain pixel can be done through the API function GetPixel; setting the color of a certain point can be done through SetPixel.

(3) Beneficial effects

Compared with the prior art, the present invention has the following beneficial effects: a nano-scale mud shale digital core construction method of the present invention can solve the problem of small pore throats in unconventional reservoirs such as mud shale and the existence of a large number of nano-scale micro-cracks It is difficult to describe the distribution of pores and reflect the characteristics of pore structure in digital cores established by conventional methods and ordinary CT scanning technology. The invention provides a better research platform for the numerical simulation research of the rock physical properties of unconventional reservoirs, and thus has high popularization value and social benefits. There is no proposal and application of a similar method in the current published literature and commercial application software.

Description of drawings

Fig. 1 is a schematic diagram of the manufacturing steps of the present invention;

Fig. 2 is the sample cutting area selected by the specific implementation case of the present invention;

Fig. 3 (a) is the digital rock core image before registration of the specific implementation case of the present invention;

Fig. 3 (b) is the digital rock core image after the registration of the specific implementation case of the present invention;

Fig. 4 (a) is the digital rock core image before angle correction of the specific implementation case of the present invention;

Fig. 4 (b) is the digital rock core image after the angle correction of the concrete implementation case of the present invention;

Fig. 5 (a) is the digital rock core image before shading correction of the specific implementation case of the present invention;

Fig. 5 (b) is the digital rock core image after shading correction of the specific implementation case of the present invention;

Figure 6. Nanometer resolution mud shale digital core constructed after processing.

Detailed ways

As shown in Figure 1, a nano-scale mud shale digital core construction method, firstly adopts FIB-SEM cutting and scanning technology to cut and scan the mud shale core samples, obtain a series of two-dimensional pictures of the core, and then analyze the acquired pictures The image registration technology is used to align two adjacent images, the shear transformation is used to correct the angle of the image, and the shadow correction is used to correct the image, and finally a nano-scale resolution mud shale digital core is constructed. The specific steps are as follows:

(1) Using FIB-SEM to cut and scan the core, the steps include:

a. For the plunger rock sample with a diameter of 25 mm, select an appropriate sub-sample area, cut a thin slice with a diameter of 25 mm and a thickness of 2-5 mm, then observe with an electron microscope, select the area of interest, and perform argon ion analysis on the cut end face. Light;

b. Carry out carbon coating on the scanning end face of the rock core after polishing;

c. Grind a groove on the surface of the sample, and then use FIB-SEM technology to cut and scan the area of 15 microns x 10 microns x 10 microns;

d. Scanning and cutting are carried out alternately, and the number of slices is not less than 1000 sliced images in TIFF format;

e. The computer stores and scans the images in TIFF format, and ends the experiment when a certain number of slices is reached;

(2) FIB-SEM scanning image registration: the two-dimensional image is represented by a two-dimensional numerical matrix, and I ₁ (x, y) and I ₂ (x, y) respectively represent the two images that need to be registered. The gray value at (x, y), where I ₁ is the reference image and I ₂ is the image to be registered, then the registration relationship of images I ₁ and I ₂ can be expressed as

I ₂ (x,y)=G(I ₁ (F(x,y)))

Among them, F represents a two-dimensional coordinate transformation function; G represents a one-dimensional grayscale transformation function; the main task of image registration is to find the best coordinate transformation function F, and the grayscale transformation function G, so that the difference between the two images To achieve optimal alignment, since the grayscale transformation function G does not need to be solved in most cases, obtaining the coordinate transformation function F becomes a key issue in image registration. The above formula can be simplified to the following form:

I ₂ (x, y) = I ₁ (F(x, y))

In the process of image registration, the commonly used image transformation methods mainly include rigid body transformation, affine transformation, projective transformation and nonlinear transformation; if the distance between any two points in the image remains unchanged before and after transformation, this transformation is called It is rigid body transformation; rigid body transformation can be decomposed into overall translation and rotation; in a two-dimensional image, the transformation formula of coordinate point (x, y) to point (x′, y′) through rigid body transformation is:

in is the rotation angle, Δx and Δy are translation distances;

(3) Angle correction: During the cutting and scanning process of FIB-SEM, when the angle between the ion beam and the electron beam is not 90°, the cutting surface scanned by the scanning electron microscope cannot reflect the real size of the sample, so an angle transformation is required Transition to the state where the electron beam is perpendicular to the scanning surface can be calculated by the following formula:

$\mathrm{<span\; class="notranslate">\; AC</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; AB</span>}}{\mathrm{<span\; class="notranslate">\; cos</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 90</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; )</span>}$

Among them, α is the angle between the ion beam and the electron beam, AB is the size obtained by scanning, and AC is the real size of the sample;

(4) Shading correction: Due to the influence of the sample groove and the stage, it will cause certain interference to the SEM electronic signal, resulting in a partial shadow area in the image, that is to say, the area representing the same material phase has different gray values, so It is necessary to perform shading correction on the scanned image to ensure the accuracy of image segmentation; the correction method uses grayscale processing technology to perform shading correction on the image;

(5) Establishment of nanoscale mud shale digital core: the processed 2D images are superimposed to form a nanoscale resolution 3D mud shale digital core.

Wherein, the grayscale image processing technology described in step 4 is to take out the grayscale value of each pixel in the picture, and then the red, green, and blue components of the color of this point are all set as grayscale values; grayscale value=red × 0.30+green×0.59+blue×0.11; getting a certain pixel color can be done through the API function GetPixel; setting the color of a certain point can be done through SetPixel.

The present invention will be described in detail below in conjunction with the accompanying drawings and examples. The source of the project to which this example belongs is the key scientific research project of Sinopec "Evaluation and layer selection technology for mud shale oil and gas logging", and the project number is JP12022.

Specific steps are as follows:

Step 1: Use FIB-SEM to cut and scan the core

The FIB-SEM instrument used in the study is Helios 650 produced by FEI Company, with a lateral resolution of 5nm and a vertical resolution of 10nm.

The steps include: for a plug rock sample with a diameter of 25 mm, select an appropriate sub-sample area, cut a thin section with a diameter of 25 mm and a thickness of 2-5 mm, then observe with an electron microscope, select an area of interest, as shown in Figure 2, and Argon ion polishing is performed on the cutting end face; then the scanning end face of the rock core after cutting is subjected to carbon coating; a groove is ground on the surface of the sample, and then FIB-SEM technology is used to cut an area of 15 microns x 10 microns x 10 microns Scanning; scanning and cutting are performed alternately, and the number of slices is not less than 1000 slice images in TIFF format; the images in TIFF format obtained by scanning are stored, and the experiment ends when the required sample size is reached;

Step 2: FIB-SEM scan image registration

In the process of image registration, the commonly used image transformation methods mainly include rigid body transformation, affine transformation, projective transformation and nonlinear transformation. If the distance between any two points in the image remains the same before and after the transformation, the transformation is called a rigid body transformation. Rigid body transformations can be decomposed into global translations and rotations. In a two-dimensional image, the transformation formula of a coordinate point (x, y) transformed to a point (x′, y′) by a rigid body is:

in is the rotation angle, and Δx and Δy are translation distances. In this registration process, the global registration method based on image grayscale is adopted, only the translation transformation of the image is considered, and the rotation transformation is not considered, so the rotation angle Figure 3(a) is the digital core image before registration, and Figure 3(b) is the digital core image after registration. By comparison, it can be seen that the edges of the image before registration and the boundaries of each phase are jagged and jagged. After registration, the edge of the image becomes relatively smooth, which eliminates the misalignment error in the scanning process.

Step 3: Angle Correction

During the cutting and scanning process of FIB-SEM, because the angle between the ion beam and the electron beam is not 90°, the cutting surface scanned by the scanning electron microscope cannot reflect the real size of the sample, and an angle conversion is required to convert the electron beam and the scanning surface. vertical state. It can be calculated by the following formula:

$\mathrm{<span\; class="notranslate">\; AC</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; AB</span>}}{\mathrm{<span\; class="notranslate">\; cos</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 90</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; )</span>}$

Among them, α is the angle between the ion beam and the electron beam. AC is the surface of the scanned sample, and AB is the plane perpendicular to the electron beam. The actual image size scanned by the SEM is AB (the projection of AC on the AB plane), not the actual size of the sample. The angle transformation is to scan the SEM Convert the image size to the actual size of the sample. In this example, α=52°, Fig. 4(a) is the digital rock core image before angle correction, and Fig. 4(b) is the digital rock core image after angle correction.

Step 4: Shading Correction

Due to the influence of the sample groove and the stage, there may be some interference to the SEM electronic signal, resulting in a partial shadow area in the image, that is to say, the area representing the same material phase has different gray values, so it is necessary to scan the image. Shading correction To ensure the accuracy of image segmentation, the correction method is adopted.

Step 5: Build nanoscale mud shale digital core

The processed images are sequentially superimposed to form a nanoscale resolution mud shale digital core. Fig. 6 is a nanoscale resolution mud shale digital core constructed by this method, with a horizontal resolution of 5 nm and a vertical resolution of 10 nm, and a sample size of 1700*900*700.

The beneficial effect of the present invention is that it can solve the problem that unconventional reservoirs such as mud shale have small pore throats and a large number of nano-scale microcracks and micropores, which make it difficult to describe the pore distribution and difficult Reflect the problem of pore structure characteristics. The invention proposes a method for establishing digital cores of mud shale with nanoscale resolution, which provides a better research platform for numerical simulation research on rock physical properties of unconventional reservoirs, and thus has high promotion value and social benefits.

The above-mentioned embodiments are only descriptions of preferred implementations of the present invention, and are not intended to limit the concept and scope of the present invention. Under the premise of not departing from the design concept of the present invention, various modifications and improvements made by ordinary persons in the art to the technical solution of the present invention shall fall within the scope of protection of the present invention, and the technical content claimed in the present invention has been fully described in the claims.

Claims (2)

1. a nanoscale mud shale digital cores construction method, first adopt FIB-SEM to cut scanning technique and cutting scanning is carried out to mud shale core sample, obtain a series of rock core two-dimension picture, then image registration techniques is adopted to carry out registration process to adjacent two images to the picture obtained, adopt shear transformation to image just angularity correction, adopt and carry out shadow correction to image, the final mud shale digital cores building nanometer resolution, its concrete steps are as follows:

(1) utilize FIB-SEM to carry out cutting scanning to rock core, step comprises:

A. to diameter 25 millimeters of plunger rock samples, select suitable subsample region, cut diameter 25 millimeters, the thin slice of thick 2-5 millimeter, then uses electron microscopic observation, select area-of-interest, and to cutting end face just argon ion cut open light;

B. the process of painting carbon is carried out to cuing open the scanning of the rock core after light end face;

C. go out a groove in sample surfaces grinding, then use FIB-SEM technology to carry out cutting scanning to area 15 microns of x10 micron x10 um region;

D. scan incision hockets, and obtains the sectioning image that number of slices is not less than 1000 tiff formats;

E. the tiff format image that obtains of Computer Storage scanning, terminates experiment after reaching certain number of sections;

(2) FIB-SEM scan image registration: a two dimensional image two Dimension Numerical matrix is represented, if I ₁(x, y), I ₂(x, y) represents that two width need the image of registration at the gray-scale value at (x, y) place, wherein I respectively ₁for benchmark image, I ₂for image subject to registration, so image I ₁, I ₂registration relation can be expressed as

I ₂(x，y)＝G(I ₁(F(x，y)))

Wherein, F represents the coordinate transform function of two dimension; G represents one dimension greyscale transformation function; The main task of image registration is exactly find best coordinate transform function F, with greyscale transformation function G, thus make between two width images, to realize best aligning, because greyscale transformation function G in most cases does not need to solve, therefore ask for the key issue that coordinate transform function F becomes image registration, above formula can be reduced to following form:

I ₂(x，y)＝I ₁(F(x，y))

In process of image registration, the image conversion mode commonly used mainly contains rigid body translation, affined transformation, projective transformation and nonlinear transformation; If the distance in image between any two points remains unchanged before and after conversion, then this conversion is called rigid body translation; Rigid body translation can be analyzed to integral translation and rotation; In two dimensional image, coordinate points (x, y) through rigid body translation to the transformation for mula of point (x ', y ') is:

Wherein for the anglec of rotation, Δ x, Δ y are translation distance;

(3) angularity correction: FIB-SEM is in cutting scanning process, when between ion beam and electron beam, angle is not 90 °, the cut surface of scanning electron microscope scanning can not reflect the full-size(d) of sample, therefore need to do an angular transformation and be transformed into the electron beam state vertical with scanning of a surface, by formulae discovery below:

$\mathrm{AC}=\frac{\mathrm{AB}}{\cos (90-\mathrm{\&alpha;})}$

Wherein, α is the angle of ion beam and electron beam, and AB is the size that scanning obtains, and AC is the full-size(d) of sample;

(4) shadow correction: due to the impact of sample groove and objective table, certain interference can be produced to SEM electronic signal, image local is caused to occur shadow region, that is the region representing same substance phase has different gray-scale value, therefore needs to carry out shadow correction to scan image thus the accuracy of guarantee Iamge Segmentation; Bearing calibration adopts gray proces technology to carry out shadow correction to image;

(5) nanoscale mud shale digital cores is set up: the three-dimensional mud shale digital cores two dimensional image superposition after process being formed nanometer resolution.

2. a kind of nanoscale mud shale digital cores construction method according to claim 1, it is characterized in that: the gray level image treatment technology described in step 4 is the gray-scale value taking out each pixel in picture, then the red, green, blue composition of this color put all is set to gray-scale value; Gray-scale value=redness × 0.30+ green × 0.59+ blueness × 0.11; Obtain certain pixel color to be completed by api function GetPixel; The color arranging certain point can be completed by SetPixel.